FastAPI Advanced: Dependencies, Background Tasks and Middleware

This blog will teach you how to use dependencies, background tasks and middleware in FastAPI to create powerful and robust web APIs.

Table of Contents

1. Introduction

FastAPI is a modern and fast web framework for building APIs with Python. It offers many features and benefits, such as automatic documentation, data validation, asynchronous support, and more. In this blog, you will learn how to use some of the advanced features of FastAPI, such as dependencies, background tasks, and middleware.

Dependencies are a way to inject common functionality or logic into your endpoints, such as authentication, database access, caching, etc. You can define dependencies as functions or classes, and use them as parameters in your endpoint functions. FastAPI will automatically resolve and execute the dependencies, and pass the results to your endpoints.

Background tasks are a way to run some code after returning a response from your endpoint, without blocking the request. You can use background tasks to perform some long-running or heavy operations, such as sending emails, processing data, updating records, etc. You can create background tasks as functions, and add them to a special parameter in your endpoint function.

Middleware are a way to modify or intercept the request and response data before and after your endpoints. You can use middleware to add some common functionality or logic to your web application, such as logging, error handling, authentication, etc. You can create middleware as functions, and register them with your FastAPI app.

By using these advanced features, you can enhance your web API and make it more robust, secure, and efficient. In this blog, you will learn how to use dependencies, background tasks, and middleware in FastAPI with practical examples. You will also learn how to handle errors and exceptions with these features, and how to test and debug them.

Before you start, you will need to have some basic knowledge of Python and FastAPI. You will also need to install FastAPI and its dependencies, such as Uvicorn and Pydantic. You can follow the official documentation to get started with FastAPI.

Are you ready to learn how to use dependencies, background tasks, and middleware in FastAPI? Let’s begin!

2. What are Dependencies in FastAPI?

Dependencies are a powerful feature of FastAPI that allows you to inject common functionality or logic into your endpoints. You can use dependencies to perform tasks such as authentication, database access, caching, rate limiting, etc. Dependencies can help you avoid repeating code, improve performance, and simplify testing.

A dependency is a function or a class that returns some value or object that you need in your endpoint. For example, a dependency could return a database session, a current user, a configuration object, etc. You can define a dependency as a normal Python function or class, and use the Depends function from FastAPI to declare it as a parameter in your endpoint function. FastAPI will automatically resolve and execute the dependency, and pass the result to your endpoint.

For example, suppose you have a dependency function that returns the current user from a token in the request header:

from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
from pydantic import BaseModel

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

class User(BaseModel):
    username: str
    email: str
    role: str

def get_current_user(token: str = Depends(oauth2_scheme)):
    # some logic to get the user from the token
    user = User(username="alice", email="alice@example.com", role="admin")
    return user

Now, you can use this dependency in your endpoint function to get the current user:

from fastapi import FastAPI

app = FastAPI()

@app.get("/users/me")
def read_current_user(current_user: User = Depends(get_current_user)):
    return current_user

When you call this endpoint, FastAPI will first call the get_current_user function with the token from the request header, and then pass the returned user object to the read_current_user function. You can access the current user as a normal parameter in your endpoint function.

In this section, you learned what dependencies are and how to define and use them in FastAPI. In the next sections, you will learn how to share and reuse dependencies, and how to handle errors and exceptions with dependencies.

2.1. How to Define and Use Dependencies

For example, suppose you have a dependency function that returns the current user from a token in the request header:

from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
from pydantic import BaseModel

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

class User(BaseModel):
    username: str
    email: str
    role: str

def get_current_user(token: str = Depends(oauth2_scheme)):
    # some logic to get the user from the token
    user = User(username="alice", email="alice@example.com", role="admin")
    return user

Now, you can use this dependency in your endpoint function to get the current user:

from fastapi import FastAPI

app = FastAPI()

@app.get("/users/me")
def read_current_user(current_user: User = Depends(get_current_user)):
    return current_user

2.2. How to Share and Reuse Dependencies

One of the benefits of using dependencies in FastAPI is that you can share and reuse them across your endpoints. You can create common dependencies that perform tasks that are needed in multiple endpoints, such as authentication, database access, caching, etc. You can also create sub-dependencies that depend on other dependencies, and create a hierarchy of dependencies that are executed in order.

To share and reuse dependencies, you just need to define them as normal Python functions or classes, and use them as parameters in your endpoint functions with the Depends function. FastAPI will automatically resolve and execute the dependencies, and pass the results to your endpoints. You can use the same dependency in multiple endpoints, and FastAPI will cache the result of the dependency for each request, so it is only executed once.

For example, suppose you have a dependency function that returns the current user from a token in the request header, as we saw in the previous section:

from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
from pydantic import BaseModel

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

class User(BaseModel):
    username: str
    email: str
    role: str

def get_current_user(token: str = Depends(oauth2_scheme)):
    # some logic to get the user from the token
    user = User(username="alice", email="alice@example.com", role="admin")
    return user

Now, you can use this dependency in multiple endpoints that need the current user, such as:

from fastapi import FastAPI

app = FastAPI()

@app.get("/users/me")
def read_current_user(current_user: User = Depends(get_current_user)):
    return current_user

@app.put("/users/me")
def update_current_user(new_email: str, current_user: User = Depends(get_current_user)):
    # some logic to update the user's email
    current_user.email = new_email
    return current_user

FastAPI will execute the get_current_user function only once for each request, and pass the same user object to both endpoints. This way, you can avoid repeating code and improve performance.

You can also create sub-dependencies that depend on other dependencies, and create a hierarchy of dependencies that are executed in order. For example, suppose you have a sub-dependency function that checks if the current user is an admin, and raises an exception if not:

from fastapi import Depends, HTTPException, status

def get_current_admin(current_user: User = Depends(get_current_user)):
    # some logic to check if the user is an admin
    if current_user.role != "admin":
        raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="Not authorized")
    return current_user

Now, you can use this sub-dependency in endpoints that require admin privileges, such as:

@app.delete("/users/{user_id}")
def delete_user(user_id: int, current_admin: User = Depends(get_current_admin)):
    # some logic to delete the user
    return {"message": f"User {user_id} deleted"}

FastAPI will first execute the get_current_user dependency, and then pass the result to the get_current_admin sub-dependency, which will check if the user is an admin and raise an exception if not. Finally, the result of the sub-dependency will be passed to the endpoint function. This way, you can create a chain of dependencies that are executed in order.

In this section, you learned how to share and reuse dependencies in FastAPI. You also learned how to create sub-dependencies that depend on other dependencies, and create a hierarchy of dependencies that are executed in order. In the next section, you will learn how to handle errors and exceptions with dependencies.

2.3. How to Handle Errors and Exceptions with Dependencies

Dependencies are a powerful feature of FastAPI that allows you to inject common functionality or logic into your endpoints. However, sometimes dependencies can fail or raise errors or exceptions, and you need to handle them properly. For example, a dependency could fail to authenticate a user, connect to a database, or access a resource. In this section, you will learn how to handle errors and exceptions with dependencies in FastAPI.

One way to handle errors and exceptions with dependencies is to use the HTTPException class from FastAPI. This class allows you to raise an exception with a specific HTTP status code and a detail message. FastAPI will catch the exception and return a JSON response with the status code and the detail message. You can use the HTTPException class in your dependency functions to indicate that something went wrong and return an appropriate error response.

For example, suppose you have a dependency function that checks if the current user is an admin, and raises an exception if not, as we saw in the previous section:

from fastapi import Depends, HTTPException, status

def get_current_admin(current_user: User = Depends(get_current_user)):
    # some logic to check if the user is an admin
    if current_user.role != "admin":
        raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="Not authorized")
    return current_user

If you use this dependency in an endpoint that requires admin privileges, and the user is not an admin, FastAPI will return a JSON response like this:

{
  "detail": "Not authorized"
}

with a status code of 403 Forbidden. This way, you can inform the user that they are not allowed to access the endpoint, and stop the execution of the endpoint function.

Another way to handle errors and exceptions with dependencies is to use the Depends function from FastAPI. This function allows you to pass a custom exception handler function as a keyword argument, and use it to handle any exception that occurs in the dependency. The exception handler function should take the exception as a parameter, and return a response object. You can use the Depends function in your endpoint functions to specify how to handle any exception that occurs in the dependency.

For example, suppose you have a dependency function that connects to a database, and raises an exception if the connection fails:

from fastapi import Depends
from sqlalchemy import create_engine
from sqlalchemy.exc import OperationalError

engine = create_engine("sqlite:///example.db")

def get_db():
    # some logic to connect to the database
    try:
        connection = engine.connect()
        return connection
    except OperationalError as e:
        raise e

Now, you can use the Depends function in your endpoint function to pass a custom exception handler function, such as:

from fastapi import FastAPI, Response, status

app = FastAPI()

def handle_db_error(e: OperationalError):
    # some logic to handle the database error
    return Response(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, content=f"Database error: {e}")

@app.get("/items")
def read_items(db: object = Depends(get_db, handle_db_error)):
    # some logic to read items from the database
    items = db.execute("SELECT * FROM items").fetchall()
    return items

If the get_db dependency raises an exception, FastAPI will call the handle_db_error function with the exception as a parameter, and return the response object that it returns. In this case, it will return a response with a status code of 500 Internal Server Error, and a content with the database error message. This way, you can customize how to handle any exception that occurs in the dependency, and return a suitable response.

In this section, you learned how to handle errors and exceptions with dependencies in FastAPI. You learned how to use the HTTPException class to raise an exception with a specific status code and detail message, and how to use the Depends function to pass a custom exception handler function. In the next section, you will learn what background tasks are and how to use them in FastAPI.

3. What are Background Tasks in FastAPI?

Background tasks are another advanced feature of FastAPI that allows you to run some code after returning a response from your endpoint, without blocking the request. You can use background tasks to perform some long-running or heavy operations, such as sending emails, processing data, updating records, etc. Background tasks can help you improve performance, responsiveness, and user experience.

A background task is a function that takes a special parameter of type BackgroundTasks from FastAPI. This parameter is an object that allows you to add tasks to be executed in the background. You can add tasks as functions, and pass any arguments that they need. You can create background tasks as normal Python functions, and add them to the BackgroundTasks object in your endpoint function. FastAPI will run the background tasks after returning the response from your endpoint.

For example, suppose you have a background task function that sends an email to a user:

from fastapi import BackgroundTasks
import smtplib

def send_email(to: str, subject: str, body: str):
    # some logic to send an email
    server = smtplib.SMTP("smtp.example.com")
    server.login("user", "password")
    server.sendmail("user@example.com", to, f"Subject: {subject}\n\n{body}")
    server.quit()

Now, you can use this background task in your endpoint function to send an email to a user after creating an account:

from fastapi import FastAPI

app = FastAPI()

@app.post("/users")
def create_user(name: str, email: str, background_tasks: BackgroundTasks):
    # some logic to create a user
    user = User(name=name, email=email)
    background_tasks.add_task(send_email, to=email, subject="Welcome", body=f"Hello {name}, thank you for joining us!")
    return user

When you call this endpoint, FastAPI will first create the user and return the user object as a response, and then run the send_email function in the background with the email, subject, and body as arguments. This way, you can send an email to the user without delaying the response from the endpoint.

In this section, you learned what background tasks are and how to create and run them in FastAPI. In the next sections, you will learn how to access request data in background tasks, and how to test and debug them.

3.1. How to Create and Run Background Tasks

For example, suppose you have a background task function that sends an email to a user:

from fastapi import BackgroundTasks
import smtplib

def send_email(to: str, subject: str, body: str):
    # some logic to send an email
    server = smtplib.SMTP("smtp.example.com")
    server.login("user", "password")
    server.sendmail("user@example.com", to, f"Subject: {subject}\n\n{body}")
    server.quit()

Now, you can use this background task in your endpoint function to send an email to a user after creating an account:

from fastapi import FastAPI

app = FastAPI()

@app.post("/users")
def create_user(name: str, email: str, background_tasks: BackgroundTasks):
    # some logic to create a user
    user = User(name=name, email=email)
    background_tasks.add_task(send_email, to=email, subject="Welcome", body=f"Hello {name}, thank you for joining us!")
    return user

3.2. How to Access Request Data in Background Tasks

Sometimes, you may need to access some data from the request in your background tasks, such as headers, cookies, query parameters, etc. For example, you may want to log the request data, or use it to customize the background task behavior. However, you cannot directly access the request object in your background task functions, as it is not available after returning the response from the endpoint. In this section, you will learn how to access request data in background tasks in FastAPI.

One way to access request data in background tasks is to pass it as an argument to your background task function, and add it to the BackgroundTasks object in your endpoint function. You can use the Request object from FastAPI to access the request data, and extract the data that you need. You can then pass the data as a normal argument to your background task function, and use it in your background task logic.

For example, suppose you have a background task function that logs the request data to a file:

from fastapi import BackgroundTasks

def log_request_data(data: dict):
    # some logic to log the data to a file
    with open("log.txt", "a") as f:
        f.write(f"{data}\n")

Now, you can use this background task in your endpoint function to log the request data after returning the response:

from fastapi import FastAPI, Request

app = FastAPI()

@app.get("/items")
def read_items(request: Request, background_tasks: BackgroundTasks):
    # some logic to read items
    items = ["apple", "banana", "orange"]
    # extract the data that you need from the request
    data = {
        "method": request.method,
        "url": request.url,
        "headers": dict(request.headers),
        "cookies": request.cookies,
        "query_params": request.query_params
    }
    # pass the data as an argument to the background task function
    background_tasks.add_task(log_request_data, data=data)
    return items

When you call this endpoint, FastAPI will first return the items as a response, and then run the log_request_data function in the background with the data as an argument. This way, you can access the request data in your background task function, and use it for your background task logic.

Another way to access request data in background tasks is to use a dependency that returns the request data, and declare it as a parameter in your background task function with the Depends function from FastAPI. You can create a dependency function that takes the Request object as a parameter, and returns the data that you need. You can then use the Depends function in your background task function to declare the dependency as a parameter, and use it in your background task logic.

For example, suppose you have a dependency function that returns the request data as a dictionary:

from fastapi import Request

def get_request_data(request: Request):
    # extract the data that you need from the request
    data = {
        "method": request.method,
        "url": request.url,
        "headers": dict(request.headers),
        "cookies": request.cookies,
        "query_params": request.query_params
    }
    return data

Now, you can use this dependency in your background task function to access the request data:

from fastapi import BackgroundTasks, Depends

def log_request_data(data: dict = Depends(get_request_data)):
    # some logic to log the data to a file
    with open("log.txt", "a") as f:
        f.write(f"{data}\n")

And you can use this background task in your endpoint function to log the request data after returning the response:

from fastapi import FastAPI

app = FastAPI()

@app.get("/items")
def read_items(background_tasks: BackgroundTasks):
    # some logic to read items
    items = ["apple", "banana", "orange"]
    # add the background task function with the dependency
    background_tasks.add_task(log_request_data)
    return items

When you call this endpoint, FastAPI will first return the items as a response, and then run the log_request_data function in the background with the dependency. FastAPI will resolve and execute the dependency, and pass the result to the background task function. This way, you can access the request data in your background task function, and use it for your background task logic.

In this section, you learned how to access request data in background tasks in FastAPI. You learned how to pass the request data as an argument to your background task function, and how to use a dependency that returns the request data in your background task function. In the next section, you will learn how to test and debug background tasks in FastAPI.

3.3. How to Test and Debug Background Tasks

Background tasks are another advanced feature of FastAPI that allows you to run some code after returning a response from your endpoint, without blocking the request. However, testing and debugging background tasks can be challenging, as they are not part of the normal request-response cycle. In this section, you will learn how to test and debug background tasks in FastAPI.

One way to test background tasks is to use the TestClient class from FastAPI. This class allows you to create a test client that can send requests to your FastAPI app, and receive responses. You can use the TestClient class to test your endpoints and their responses, and also to test your background tasks and their effects. You can create a test client as an instance of the TestClient class, and pass your FastAPI app as an argument. You can then use the test client to send requests to your endpoints, and check the responses and the background tasks.

For example, suppose you have an endpoint that creates a user and sends an email to the user in a background task, as we saw in the previous section:

from fastapi import FastAPI, BackgroundTasks
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    name: str
    email: str

def send_email(to: str, subject: str, body: str):
    # some logic to send an email
    ...

@app.post("/users")
def create_user(user: User, background_tasks: BackgroundTasks):
    # some logic to create a user
    ...
    background_tasks.add_task(send_email, to=user.email, subject="Welcome", body=f"Hello {user.name}, thank you for joining us!")
    return user

Now, you can use the TestClient class to test this endpoint and the background task:

from fastapi.testclient import TestClient

client = TestClient(app)

def test_create_user():
    # create a test user
    test_user = {"name": "bob", "email": "bob@example.com"}
    # send a post request to the endpoint with the test user
    response = client.post("/users", json=test_user)
    # check the status code and the response data
    assert response.status_code == 200
    assert response.json() == test_user
    # check the background task effect
    # for example, check if the email was sent
    # you can use a mock email server or a library like mailtrap
    ...

This way, you can test your endpoint and the background task using the TestClient class.

Another way to debug background tasks is to use the logger object from FastAPI. This object allows you to log messages to the standard output or a file, and use them to track the execution and the errors of your background tasks. You can use the logger object to log any information that you need in your background task functions, such as the arguments, the results, the exceptions, etc. You can then use the logs to debug your background tasks and find the source of any problems.

For example, suppose you have a background task function that logs the request data to a file, as we saw in the previous section:

from fastapi import BackgroundTasks

def log_request_data(data: dict):
    # some logic to log the data to a file
    ...

Now, you can use the logger object to log some information in your background task function, such as:

from fastapi import BackgroundTasks, logger

def log_request_data(data: dict):
    # log the data that is passed to the function
    logger.info(f"Received data: {data}")
    # some logic to log the data to a file
    try:
        with open("log.txt", "a") as f:
            f.write(f"{data}\n")
        # log the success message
        logger.info("Data logged successfully")
    except Exception as e:
        # log the exception message
        logger.error(f"Data logging failed: {e}")

Then, you can use the logs to debug your background task function, and see if it is working as expected, or if there are any errors or exceptions.

In this section, you learned how to test and debug background tasks in FastAPI. You learned how to use the TestClient class to test your endpoints and their responses, and also to test your background tasks and their effects. You also learned how to use the logger object to log messages to the standard output or a file, and use them to debug your background tasks and find the source of any problems.

4. What are Middleware in FastAPI?

Middleware are another advanced feature of FastAPI that allows you to modify or intercept the request and response data before and after your endpoints. You can use middleware to add some common functionality or logic to your web application, such as logging, error handling, authentication, etc. Middleware can help you improve security, performance, and consistency.

A middleware is a function that takes two parameters: a request object and a call_next function. The request object contains the request data, such as headers, cookies, query parameters, etc. The call_next function is a function that receives the request and returns the response. You can create a middleware as a normal Python function, and use the app.middleware decorator from FastAPI to register it with your FastAPI app. FastAPI will execute the middleware for every request to your app.

For example, suppose you have a middleware function that logs the request and response data to a file:

from fastapi import FastAPI

app = FastAPI()

@app.middleware("http")
async def log_middleware(request, call_next):
    # log the request data
    with open("log.txt", "a") as f:
        f.write(f"Request: {request.method} {request.url}\n")
    # call the next middleware or endpoint
    response = await call_next(request)
    # log the response data
    with open("log.txt", "a") as f:
        f.write(f"Response: {response.status_code}\n")
    # return the response
    return response

Now, you can use this middleware in your app to log the request and response data for every request:

@app.get("/items")
def read_items():
    # some logic to read items
    items = ["apple", "banana", "orange"]
    return items

When you call this endpoint, FastAPI will first execute the log_middleware function with the request and the call_next function as arguments. The middleware function will log the request data to a file, and then call the call_next function with the request. The call_next function will return the response from the endpoint, and the middleware function will log the response data to a file, and then return the response to the client. This way, you can modify or intercept the request and response data with your middleware function.

In this section, you learned what middleware are and how to create and use them in FastAPI. In the next sections, you will learn how to modify request and response data with middleware, and how to handle errors and exceptions with middleware.

4.1. How to Add and Use Middleware

For example, suppose you have a middleware function that logs the request and response data to a file:

from fastapi import FastAPI

app = FastAPI()

@app.middleware("http")
async def log_middleware(request, call_next):
    # log the request data
    with open("log.txt", "a") as f:
        f.write(f"Request: {request.method} {request.url}\n")
    # call the next middleware or endpoint
    response = await call_next(request)
    # log the response data
    with open("log.txt", "a") as f:
        f.write(f"Response: {response.status_code}\n")
    # return the response
    return response

Now, you can use this middleware in your app to log the request and response data for every request:

@app.get("/items")
def read_items():
    # some logic to read items
    items = ["apple", "banana", "orange"]
    return items

4.2. How to Modify Request and Response Data with Middleware

Middleware are a way to modify or intercept the request and response data before and after your endpoints. You can use middleware to add some common functionality or logic to your web application, such as logging, error handling, authentication, etc. In this section, you will learn how to modify the request and response data with middleware in FastAPI.

To modify the request and response data with middleware, you need to use the starlette.requests.Request and starlette.responses.Response objects from the Starlette framework, which FastAPI is based on. These objects provide methods and attributes to access and manipulate the request and response data, such as headers, cookies, body, status code, etc.

For example, suppose you want to add a custom header to every response from your web application. You can create a middleware function that takes the request object as a parameter, and returns a response object. Inside the middleware function, you can use the request.headers attribute to access the request headers, and the response.headers attribute to modify the response headers. You can also use the await request.body() method to access the request body, and the response.body attribute to modify the response body. You can use the async with request syntax to ensure that the request is properly closed after the middleware function.

from fastapi import FastAPI
from starlette.requests import Request
from starlette.responses import Response

app = FastAPI()

@app.middleware("http")
async def add_custom_header(request: Request, call_next):
    # access the request headers
    print(request.headers)
    # access the request body
    print(await request.body())
    # call the next middleware or endpoint function
    response = await call_next(request)
    # modify the response headers
    response.headers["X-Custom-Header"] = "Some value"
    # modify the response body
    response.body = response.body + b"\nModified by middleware"
    # return the response object
    return response

Now, every response from your web application will have a custom header and a modified body. You can use the same technique to modify other aspects of the request and response data, such as cookies, status code, etc.

In this section, you learned how to modify the request and response data with middleware in FastAPI. In the next section, you will learn how to handle errors and exceptions with middleware in FastAPI.

4.3. How to Handle Errors and Exceptions with Middleware

Middleware are a way to modify or intercept the request and response data before and after your endpoints. You can use middleware to add some common functionality or logic to your web application, such as logging, error handling, authentication, etc. In this section, you will learn how to handle errors and exceptions with middleware in FastAPI.

To handle errors and exceptions with middleware, you need to use the starlette.exceptions.HTTPException class from the Starlette framework, which FastAPI is based on. This class allows you to raise an exception with a specific status code and detail message, which will be returned as a JSON response to the client. You can also use the fastapi.exceptions.HTTPException class, which is a subclass of the Starlette class, and provides some additional features, such as headers and background tasks.

For example, suppose you want to create a middleware function that checks if the request has a valid API key in the header, and raises an exception if not. You can create a middleware function that takes the request object as a parameter, and returns a response object. Inside the middleware function, you can use the request.headers attribute to access the request headers, and the HTTPException class to raise an exception. You can also use the async with request syntax to ensure that the request is properly closed after the middleware function.

from fastapi import FastAPI, HTTPException

app = FastAPI()

@app.middleware("http")
async def check_api_key(request: Request, call_next):
    # access the request headers
    api_key = request.headers.get("X-API-Key")
    # check if the api key is valid
    if api_key != "secret":
        # raise an exception with a status code and a detail message
        raise HTTPException(status_code=401, detail="Invalid API key")
    # call the next middleware or endpoint function
    response = await call_next(request)
    # return the response object
    return response

Now, if you call any endpoint without a valid API key in the header, you will get a 401 Unauthorized response with a JSON message:

{
  "detail": "Invalid API key"
}

You can use the same technique to handle other types of errors and exceptions with middleware, such as 404 Not Found, 500 Internal Server Error, etc. You can also customize the exception class and the response format according to your needs.

In this section, you learned how to handle errors and exceptions with middleware in FastAPI. In the next section, you will learn how to test and debug your middleware functions.

5. Conclusion

In this blog, you learned how to use some of the advanced features of FastAPI, such as dependencies, background tasks, and middleware. You learned how to define and use dependencies to inject common functionality or logic into your endpoints, such as authentication, database access, caching, etc. You learned how to share and reuse dependencies, and how to handle errors and exceptions with dependencies. You learned how to create and run background tasks to perform some long-running or heavy operations after returning a response from your endpoint, such as sending emails, processing data, updating records, etc. You learned how to access request data in background tasks, and how to test and debug background tasks. You learned how to add and use middleware to modify or intercept the request and response data before and after your endpoints, such as logging, error handling, authentication, etc. You learned how to modify request and response data with middleware, and how to handle errors and exceptions with middleware.

By using these advanced features, you can enhance your web API and make it more robust, secure, and efficient. FastAPI provides a simple and elegant way to use dependencies, background tasks, and middleware, with minimal code and maximum performance. You can use these features to create powerful and complex web applications with FastAPI.

We hope you enjoyed this blog and learned something new and useful. If you have any questions, feedback, or suggestions, please feel free to leave a comment below. Thank you for reading!